| POET: a portable approach to minimizing energy under soft real-time constraints C Imes, DHK Kim, M Maggio, H Hoffmann 21st IEEE Real-Time and Embedded Technology and Applications Symposium, 75-86, 2015 | 149 | 2015 |
| Caloree: Learning control for predictable latency and low energy N Mishra, C Imes, JD Lafferty, H Hoffmann ACM SIGPLAN Notices 53 (2), 184-198, 2018 | 142 | 2018 |
| Racing and pacing to idle: Theoretical and empirical analysis of energy optimization heuristics DHK Kim, C Imes, H Hoffmann 2015 IEEE 3rd international conference on cyber-physical systems, networks …, 2015 | 78 | 2015 |
| Energy-efficient application resource scheduling using machine learning classifiers C Imes, S Hofmeyr, H Hoffmann Proceedings of the 47th International Conference on Parallel Processing, 1-11, 2018 | 50 | 2018 |
| Minimizing energy under performance constraints on embedded platforms: resource allocation heuristics for homogeneous and single-ISA heterogeneous multi-cores C Imes, H Hoffmann ACM SIGBED Review 11 (4), 49-54, 2015 | 37 | 2015 |
| Copper: Soft real-time application performance using hardware power capping C Imes, H Zhang, K Zhao, H Hoffmann 2019 IEEE International Conference on Autonomic Computing (ICAC), 31-41, 2019 | 36 | 2019 |
| Bard: A unified framework for managing soft timing and power constraints C Imes, H Hoffmann 2016 International Conference on Embedded Computer Systems: Architectures …, 2016 | 30 | 2016 |
| Proteus: Language and runtime support for self-adaptive software development S Barati, FA Bartha, S Biswas, R Cartwright, A Duracz, D Fussell, ... IEEE Software 36 (2), 73-82, 2019 | 21 | 2019 |
| A portable interface for runtime energy monitoring C Imes, L Bergstrom, H Hoffmann Proceedings of the 2016 24th ACM SIGSOFT International Symposium on …, 2016 | 19 | 2016 |
| Pipeedge: Pipeline parallelism for large-scale model inference on heterogeneous edge devices Y Hu, C Imes, X Zhao, S Kundu, PA Beerel, SP Crago, JP Walters 2022 25th Euromicro Conference on Digital System Design (DSD), 298-307, 2022 | 13 | 2022 |
| Pipeline parallelism for inference on heterogeneous edge computing Y Hu, C Imes, X Zhao, S Kundu, PA Beerel, SP Crago, JPN Walters arXiv preprint arXiv:2110.14895, 2021 | 13 | 2021 |
| Handing dvfs to hardware: Using power capping to control software performance C Imes, H Zhang, K Zhao, H Hoffmann Technical Report, 2018 | 9 | 2018 |
| Portable multicore resource management for applications with performance constraints C Imes, DHK Kim, M Maggio, H Hoffmann 2016 IEEE 10th International Symposium on Embedded Multicore/Many-core …, 2016 | 9 | 2016 |
| A case study and characterization of a many-socket, multi-tier NUMA HPC platform C Imes, S Hofmeyr, DID Kang, JP Walters 2020 IEEE/ACM 6th Workshop on the LLVM Compiler Infrastructure in HPC (LLVM …, 2020 | 5 | 2020 |
| Arvind, Dung Nguyen, Krishna V. Palem, Yan Pei, Keshav Pingali, Ryuichi Sai, Andrew Wright, Yao-Hsiang Yang, and Sizhuo Zhang. 2019. Proteus: Language and Runtime Support for … S Barati, FA Bartha, S Biswas, R Cartwright, A Duracz, D Fussell, ... IEEE Software 36 (2), 73-82, 2019 | 5 | 2019 |
| Quantpipe: Applying adaptive post-training quantization for distributed transformer pipelines in dynamic edge environments H Wang, C Imes, S Kundu, PA Beerel, SP Crago, JP Walters ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 4 | 2023 |
| Goal: Supporting general and dynamic adaptation in computing systems A Pervaiz, YH Yang, A Duracz, F Bartha, R Sai, C Imes, R Cartwright, ... Proceedings of the 2022 ACM SIGPLAN International Symposium on New Ideas …, 2022 | 3 | 2022 |
| Controlling AI Engines in Dynamic Environments N Mishra, C Imes, H Hoffmann, JD Lafferty Published: Architectural Support for Programming Languages and Operating …, 2018 | 3 | 2018 |
| Compiler abstractions and runtime for extreme-scale sar and cfd workloads C Imes, A Colin, N Zhang, A Srivastava, V Prasanna, JP Walters 2020 IEEE/ACM Fifth International Workshop on Extreme Scale Programming …, 2020 | 2 | 2020 |
| A Portable Interface for Runtime Energy Monitoring: Extended Analysis C Imes, L Bergstrom, H Hoffmann Tech. rep. TR-2016-08. University of Chicago, Department of Computer Science, 2016 | 2 | 2016 |
